关键词: 混合高斯模型, C-V模型, 高斯核函数, 边缘停止函数, 初始化曲线

Abstract: Aiming at the problems that the target tracking is easily disturbed by the environment, this paper proposes a new algorithm based on Gaussian mixture model and the improved C-V（Chan-Vese） model. Firstly, the paper uses Gaussian mixture model to update the background and detect the contour of the moving target. Then, it does post-processing on the extracted target contour and calibrates the center of the moving target and the moving target region. Finally, the moving target region is used as the initialized curve and the improved C-V model is proposed to fit the moving target. Experimental results demonstrate that using the calibration movement target area as the initialized curve can effectively improve the convergence rate of the contour curve. Besides the segmentation of improved model is better than C-V model and LCV model in the uneven gray image and noise image.

Key words: Gaussian mixture model, C-V model, Gaussian kernel function, edge stop function, initialization curve